The MIT Energy Initiative has developed an innovative modeling tool called Macro that’s transforming how planners approach energy infrastructure development. As electricity demand surges due to AI technologies and widespread electrification, this sophisticated software enables utility planners, regulators, and researchers to navigate the complex landscape of future energy needs while balancing reliability, cost, and emissions targets.
Meeting the Growing Challenges of Energy Infrastructure Planning
Today’s utility planners face unprecedented challenges. Electricity demand is skyrocketing as data centers multiply and electrification extends to vehicles, buildings, and industrial processes. The Princeton University’s Net-Zero America study projects that U.S. electricity demand could double by 2050, requiring massive infrastructure expansion.
Adding to this complexity, thousands of intermittent renewable energy projects are coming online, necessitating complementary power sources and storage facilities. Critical facilities like hospitals and manufacturing centers demand unwavering reliability, all while carbon reduction goals become increasingly stringent.
Macro addresses these challenges by enabling planners to input detailed specifications about generating units, projected demand patterns, cost structures, emerging technologies, and policy constraints. This comprehensive approach allows for thorough exploration of infrastructure design options that optimize both economic and environmental outcomes.
Macro’s Evolution from Previous MIT Models
Macro represents the next generation in capacity expansion models (CEMs), building upon MIT’s earlier innovations. The tool’s development journey began with GenX in 2017, which focused on power system investment and grid operation decisions. In 2021, DOLPHYN expanded this framework to include hydrogen production, biofuels, and additional energy sectors.
The development team—led by MITEI research scientist Ruaridh Macdonald in collaboration with Princeton University’s Jesse Jenkins and New York University’s Dharik Mallapragada—recognized the need for larger, higher-resolution models to generate more accurate policy and technology impact assessments. Princeton collaborators Filippo Pecci and Luca Bonaldo contributed to the new architecture that provides these enhanced capabilities.
Technical Innovations That Set Macro Apart
What makes Macro revolutionary is its modular design based on four core components that describe fundamental actions in any energy system: transfer, storage, transformation, and network entry/exit. This architecture enables unprecedented flexibility, allowing users to model electricity systems alongside commodity and data networks.
Unlike traditional single-computer modeling software, Macro can decompose large problems into smaller components that run on separate machines. This makes it ideal for high-performance computing clusters and enables more accurate solutions for complex aspects like transmission planning. By separating transmission calculations from the broader optimization problem, Macro can employ specialized AI techniques for superior results.
The development team prioritized user experience, creating a taxonomy of potential users with streamlined workflows for each group. Most users can simply input data through familiar tools like Excel, while modelers who need to incorporate new technologies or policies require minimal coding. A graphical interface is currently under development to further simplify interaction for non-technical users.
Real-World Applications and Early Adoption
Macro’s flexibility has already attracted research teams working on diverse applications. Some groups are using the tool to model cement production and chemical manufacturing processes. The software has been tested internationally by collaborators in the United States, South Korea, India, and China, with several teams developing country-specific and regional models.
For example, utility planners in regions experiencing rapid growth in data centers—such as Northern Virginia, where data centers consume over 20% of the electricity supply—can use Macro to evaluate how different infrastructure investments might accommodate this demand while maintaining grid stability and meeting emissions targets.
Future Direction: Real-Time Policy Guidance
Christopher Knittel, Professor at MIT Sloan School of Management, envisions using Macro to guide energy policy development in real-time. Inspired by MIT’s global climate simulator